Python, Black,Scholes, Calc, GitHub,

https://github.com/search?l=Python&q=BlackScholes&type=Repositories

1. Python MonteCarlo

It's just a proof of concept of using TensorFlow to compute quantitative finance problems

• Model: Black-Scholes
• Method: Monte Carlo
• Language: Python with TensorFlow

https://github.com/croquelois/BlackScholesMC-TF

2. Python

Benchmark computing Black Scholes formula using different technologies

https://github.com/IntelPython/BlackScholes_bench

3. Python

pyOptionPricing, binomial, BlackScholes, garman_klass_vol, historical_vol

https://github.com/boyac/pyOptionPricing

4. Python. Jupiter

https://github.com/jknaudt21/Option-Scraper-BlackScholes

5. Python. Jupiter

Download this repository and put it somewhere appropriate on your computer. Bookmark the address of the repository as we will use it to share additional files on the day. In it, you will find the following files to help you prepare for the day:

1. introQF_warmup.ipynb a Jupyter notebook that runs through the python commands we will use during the weekend. We will not use classes but we will use lists manipulations, as well as numpy and matplotlib. If you haven't used those before we strongly recommend you go through this notebook and read up on those topics.
2. intrQF_introprobability.pdf a short document on basic probability theory that we will use extensively on the day. Most of you should be familiar with this, if not, we recommend you go through the document and make sure everything is clear.

https://github.com/nwihardjo/BlackScholes-Pricer

6. Python. Jupiter

Can an artificial neural network learn the Black Scholes option pricing formula .... yes, and quite easily. This problem will be used as a starting point for implementing neural architecture search (NAS). See the following two papers Neural Architecture Search With Reinforcement Learning and Efficient Neural Architecture Search via Parameter Sharing for an overview.

See here for an overview of the Black Scholes formula.

Notebook (Option_Data.ipynb) creates a dataset of approximately 1 million examples by pricing a call option using the Black Scholes formula over a range of possible parameters. This dataset will be used to train the neural network.

Notebook (BS_Keras.ipynb) implements a simple feed forward neural network using Keras to approximate the Black Scholes formula. It achieves a fairly high accuracy after a minimal amount of training time.

Notebook(BS_RandomSearch.ipynb) uses the GridSearch library from Scikit-learn to perform a non-exhaustive hyperparameter search (i.e., different optimizers).

Future notebooks will compare different libraries that allow you to search more parameters and/or are directed, such as Talos, Hyperas, Auto-Keras, and DARTS.

https://github.com/cshannonn/blackscholes_nas

7 Python

Implementation of Monte Carlo simulations and Black-Scholes method to calculate prices for American and European options respectively.

https://www.shashan.info/blog/option-pricing-part-2-european

https://www.shashan.info/blog/option-pricing-part-2-european

https://github.com/shashank-khanna/Option-Pricing

8 Python

Quantsbin 1.0.3, which started as a weekend project is currently in its initial phase and incorporates tools for pricing and plotting of vanilla option prices, greeks and various other analysis around them. We are working on optimising calculations and expanding the scope of library in multiple directions for future releases.

1. Option payoff, premium and greeks calculation for vanilla options on Equity, FX, Commodity and Futures.
2. Capability to calculate greeks numerically for all models and also analytically for Black Scholes Model.
3. Price vanilla options with European expiry using BSM, Binomial tree and MonteCarlo with option to incorporate continuous compounded dividend yield for Equity options, cost and convenience yield for Commodity options and local and foreign risk-free rate in case of FX options. It also allows option to give discrete dividends in cased of Equity options.
4. Price vanilla options with American expiry using Binomial tree and MonteCarlo(Longstaff Schwartz) method. There is option to provide discrete dividends for Equity options for both the models.
5. Implied volatility calculation under BSM framework model.
6. Option to create user defined or standard strategies using multiple single underlying options and directly generate and plot valuation and greeks for these strategies.

https://github.com/quantsbin/Quantsbin

9 Python

1. Make a BS model for option pricing and IV calculation
2. Make a simple and quick interface to see how price/iv/greeks change when any one of the input parameter changes.

https://github.com/flios/blackscholes

10 Python 

BS Indian Market

https://github.com/aeron7/nsepython

https://github.com/aeron7/blackscholes

11 Python

This is a Python lib implementing Black and Scholes model.

https://github.com/gbonesso/blackscholes

12 Python, Jupiter

https://github.com/soheelhaque/black_scholes

13 Python Small

https://github.com/chrissmithers/BlackScholes

14 Python

Python codes to implement basic European option valuation using Black Scholes equations.

Greeks and others

https://github.com/ganesh-k-sahu/BlackScholes

15 Python

The purpose of this model is to determine the price of a vanilla European call and put options (option that can only be exercised at the end of its maturity) based on price variation over time and assuming the asset has a lognormal distribution. 

https://github.com/joe-cipolla/blackscholes

16 Python

charts, surface

https://github.com/hotero001/BlackScholes/blob/master/BTCSBlackScholesEquation.py

17 Python

Greeks, payoff, MonteCarlo

https://github.com/alejandrobetancourt/BlackScholes

18 Python

mysql connector, Dates. Calendar

https://github.com/krzysiekbienias/BlackScholes

19 Python

BS model simple

https://github.com/vishnumenon/BlackScholes

20 Python

BS MonteCarlo

https://github.com/brodyu/BlackScholesMonteCarlo

21 Python

Calculates the Black Scholes Option Price of Bitcoin

https://github.com/ginward/BlackScholesBitcoin

22 Python

Pricing Simulations

https://github.com/wenjin-cao822/BlackScholes_Pricing_Simulations

23 Python

Screener

https://github.com/rmcwhorter/blackScholesArb

24 Python

A simple program that takes the inputs of the Black Scholes Model and calculates the call and put option prices using Python.

https://github.com/Zubin38/BlackScholesCalculator

25 Python

Price, Greeks, MonteCarlo

https://github.com/krzysiekbienias/BlackScholesWorld

26 Python

DwPrice

https://github.com/chalermporn17PPA/DW.BlackScholes

27 Python

Excell

https://github.com/jjn77/BlackScholesBot

28 Python

Black-Scholes-Merton model

We want to be able to calculate the price of an European call and an European put option, provided we know the parameters that the model should adhere to. Furthermore, if we enter all but the volatility of the stock and a market price for a European call option, we want to be able to calculate the volatility that would have yielded the correct option price using the formula. This volatility is called the implied volatility. Since there is no direct formula to solve for the implied volatility we have implemented the bisection root-finding algorithm.

Heston model

We want to be able to calculate the price of a European call option using both numerical methods for the integrals and using Monte Carlo methods. Also, to be able to calibrate the model provided you enter marketprices of European call options. This will be done using the Differential Evolution algorithm. Also, it should be able to determine the price of some complex exotic options.

https://github.com/sandershortway/BlackScholesHeston

29 Python

Solve BS Eqation

https://github.com/Aravindan98/BlackScholes-Heston/blob/main/BlackScholes7.pdf

https://github.com/Aravindan98/BlackScholes-Heston/blob/main/FULLTEXT02.pdf

https://github.com/Aravindan98/BlackScholes-Heston

30 Python

Greek, Calendar

https://github.com/krzysiekbienias/BlackScholesModel

31 Python

PDF Probability

https://github.com/Texas-UCF/BlackScholesPDF

32 Python

BSM

https://github.com/Vamsikrishnakurella/BlackScholes-model-Python-3

33 Python

Deep Learning of High-Dimensional Partial Differential Equations

This library allows you to experiment with the Deep Galerkin algorithm. For finding a PDE or ODE solution you simply define a loss function. Then, by calling train(), the neural network learns the solution. It outputs several useful information:

https://arxiv.org/abs/1708.07469

https://github.com/pooyasf/DGM

34 Python, R

Greeks

https://github.com/ALANHENG/Robot

35 Python, Jupiter

pyBlackScholesAnalytics package is a Python package designed to use the well known Black-Scholes model to evaluate price, P&L and greeks of European options (both plain-vanilla and simple equity exotics such as cash-or-nothing Digital options), as well as simple option strategies built on them.

https://github.com/gabrielepompa88/pyBlackScholesAnalytics

36 Py, C, c from py

https://github.com/trevorc/blackscholes